The goal of machine learning is to
program computers to use example data or past experience to solve a given
problem. Many successful applications of machine learning exist already,
including systems that analyze past sales data to predict customer behavior,
optimize robot behavior so that a task can be completed using minimum
resources, and extract knowledge from bioinformatics data. Introduction to
Machine Learning is a comprehensive textbook on the subject, covering a
broad array of topics not usually included in introductory machine learning
texts. In order to present a unified treatment of machine learning problems and
solutions, it discusses many methods from different fields, including
statistics, pattern recognition, neural networks, artificial intelligence,
signal processing, control, and data mining. All learning algorithms are
explained so that the student can easily move from the equations in the book to
a computer program.

The text covers such topics as supervised learning,
Bayesian decision theory, parametric methods, multivariate methods, multilayer
perceptrons, local models, hidden Markov models, assessing and comparing
classification algorithms, and reinforcement learning. New to the second edition are chapters on kernel machines, graphical
models, and Bayesian estimation; expanded coverage of statistical tests in a
chapter on design and analysis of machine learning experiments; case studies
available on the Web (with downloadable results for instructors); and many
additional exercises. All chapters have been revised and updated.

Introduction to Machine Learning can be used by
advanced undergraduates and graduate students who have completed courses in
computer programming, probability, calculus, and linear algebra. It will also
be of interest to engineers in the field who are concerned with the application
of machine learning methods.

Errata:

·p. 41: Fourth line
from the bottom of the page: “ic” should be “is” (Alexander Moriarty)

·p. 66: Fourth line
from the top of the page: “negligible” is misspelled (Bugra Akyildiz)